TANGO-SEC
Trustworthy AI in Next Generation cOmmunications: SECurity and Privacy
Workshop Chairs
- → Kapal Dev
- → Rashid Ali
- → Sunder Ali Khowaja
Detail TANGO-SEC 01/04
TANGO-SEC 2026 focuses on the security and privacy implications of AI-native next-generation communication systems such as 6G, Wi-Fi 7/8, non-terrestrial networks, and virtualized telecom infrastructures. While federated learning and generative AI promise better automation and optimization, they also introduce new attack surfaces that go beyond traditional protocol weaknesses, including model inversion, poisoned gradients, evasion attacks, side-channel leakage, and manipulation of autonomous network orchestration. The workshop aims to bridge the AI/ML and critical infrastructure communities by examining adversarial threats against the intelligence layer of communication networks and by exploring mitigations that improve availability, reliability, and security in AI-driven communication stacks.
Topics of interest include, but are not limited to 02/04
- GenAI for generating poisoning samples against Network Slice Selection Functions
- Model inversion attacks on xApps and rApps in O-RAN architecture
- Backdoor injections in pre-trained models used for channel state information feedback
- Evasion attacks against AI-based intrusion detection in virtualized EPC/5GC
- Side-channel attacks on GPU/TPU accelerators used for real-time inference in edge nodes
- Homomorphic encryption for verifiable FL averaging in untrusted MEC hosts
- Differential privacy calibration for network telemetry data without utility loss
- Adversarial training methods robust to both Gaussian noise and structured poisoning
- Testbeds and datasets for evaluating data/model attacks in NFV orchestration
- Formal verification of AI controllers for network slicing against safety violations
- Impact assessment of model corruption on SLAs and QoE
- Legal implications of AI-generated fake network telemetry data
- Zero-trust architecture applied to MLOps pipelines in telecom industry
- Explainable AI (XAI) for auditing black-box network optimizers
Workshop Chairs 03/04
Workshop Chairs
Program Committee
Submission 04/04
Submission Guidelines
The submission guidelines valid for the workshop are the same as for the ARES conference.